Artificial Intelligence Application

Understand and apply artificial intelligence (AI) to technological artifacts, while assessing its benefits and challenges.



Competency Area

Artificial Intelligence


Understands the three areas of AI

Understands basic AI terminologies and concepts, specifically related to the three key areas of cognitive systems, robotics, and machine learning

Recognises and utilises established definitions of AI for informed research on AI

Aware of knowledge representations (how computers represent knowledge)

Identifies and differentiates between technologies that use and do not use AI

Distinguishes between technological artifacts that use / don’t use AI

Analyses the various features that make an entity intelligent, including the differences between human, animal, and machine intelligence

Identifies technologies that use AI (technology spanning cognitive systems, robotics, machine learning, etc.)

Recognises knowledge representation, including how computers reason and make decisions

Understands basic data literacy concepts and links them to machine learning

Identifies and differentiates between technologies that use and do not use AI

Understands that there are multiple ways of developing ‘intelligent’ machines

Demonstrates the strengths and weaknesses of AI by identifying problem types that AI excels at versus problems that are more challenging

Provides examples of knowledge representations (how computers represent knowledge)

Interprets AI data keeping in mind the role humans play in programming, choosing models, and fine-tuning AI systems

Proposes potential applications of AI and evaluates their impact

Designs AI-focused solutions

Guides the team on when it is appropriate to use AI and when to leverage human skills

Designs AI-focused solutions that are capable of disrupting current systems (service delivery and information technology systems, organisational behaviour, decision-making processes, etc.)

Creates iterative processes with feedback loops that promote quick internal learning

Develop processes to monitor the physical impact of AI on the world, including their action versus reaction capabilities

Understands the criticality of ethics in AI

Articulates an AI vision

Designs technology roadmaps to gain strategic advantage through the use of AI

Promotes transparency in all aspects of AI design

Cultivates discussions on key ethical issues surrounding AI (privacy, transparency, accountability, etc.)

Considers how perceptions of AI affect individuals differently based on parameters like age, prior experience with technology, gender, etc.

Articulates an AI vision to achieve buy-in, and motivate the exploration of AI use-cases with uncertain outcomes